Machine Learning Predictive Model to Guide Treatment Allocation for Recurrent Hepatocellular Carcinoma After Surgery
Authors: Simone Famularo, Matteo Donadon, Federica Cipriani, Federico Fazio, Francesco Ardito, Maurizio Iaria, Pasquale Perri, Simone Conci, Tommaso Dominioni, Quirino Lai, Giuliano La Barba, Stefan Patauner, Sarah Molfino, Paola Germani, Giuseppe Zimmitti, Enrico Pinotti, Matteo Zanello, Luca Fumagalli, Cecilia Ferrari, Maurizio Romano, Antonella Delvecchio, Maria Grazia Valsecchi, Adelmo Antonucci, Fabio Piscaglia, Fabio Farinati, Yoshikuni Kawaguchi, Kiyoshi Hasegawa, Riccardo Memeo, Giacomo Zanus, Guido Griseri, Marco Chiarelli, Elio Jovine, Mauro Zago, Moh’d Abu Hilal, Paola Tarchi, Gian Luca Baiocchi, Antonio Frena, Giorgio Ercolani, Massimo Rossi, Marcello Maestri, Andrea Ruzzenente, Gian Luca Grazi, Raffaele Dalla Valle, Fabrizio Romano, Felice Giuliante, Alessandro Ferrero, Luca Aldrighetti, Davide P. Bernasconi, Guido Torzilli, GUIDO COSTA, FLAVIO MILANA, FRANCESCA RATTI, NADIA RUSSOLILLO, FRANCESCO RAZIONALE, ALESSANDRO GIANI, FRANCESCA CARISSIMI, MARIO GIUFFRIDA, VALERIO DE PEPPO, IVAN MARCHITELLI, FRANCESCA DE STEFANO, ZOE LARGHI LAURERIO, ALESSANDRO CUCCHETTI, FRANCESCA NOTTE, DAVIDE COSOLA, PIO CORLEONE, ALBERTO MANZONI, MAURO MONTUORI, ANGELO FRANCESCHI, LUCA SALVADOR, MARIA CONTICCHIO, MARCO BRAGA, SILVIA MORI
Journal: JAMA Surgery (2022)

Clear indications on how to select retreatments for recurrent hepatocellular carcinoma (HCC) are still lacking.To create a machine learning predictive model of survival after HCC recurrence to allocate patients to their best potential treatment.Real-life data were obtained from an Italian registry of hepatocellular carcinoma between January 2008 and December 2019 after a median (IQR) follow-up of 27 (12-51) months. External validation was made on data derived by another Italian cohort and a Japanese cohort. Patients who experienced a recurrent HCC after a first surgical approach were included. Patients were profiled, and factors predicting survival after recurrence under different treatments that acted also as treatment effect modifiers were assessed. The model was then fitted individually to identify the best potential treatment. Analysis took place between January and April 2021.Patients were enrolled if treated by reoperative hepatectomy or thermoablation, chemoembolization, or sorafenib.Survival after recurrence was the end point.A total of 701 patients with recurrent HCC were enrolled (mean [SD] age, 71 [9] years; 151 [21.5%] female). Of those, 293 patients (41.8%) received reoperative hepatectomy or thermoablation, 188 (26.8%) received sorafenib, and 220 (31.4%) received chemoembolization. Treatment, age, cirrhosis, number, size, and lobar localization of the recurrent nodules, extrahepatic spread, and time to recurrence were all treatment effect modifiers and survival after recurrence predictors. The area under the receiver operating characteristic curve of the predictive model was 78.5% (95% CI, 71.7%-85.3%) at 5 years after recurrence. According to the model, 611 patients (87.2%) would have benefited from reoperative hepatectomy or thermoablation, 37 (5.2%) from sorafenib, and 53 (7.6%) from chemoembolization in terms of potential survival after recurrence. Compared with patients for which the best potential treatment was reoperative hepatectomy or thermoablation, sorafenib and chemoembolization would be the best potential treatment for older patients (median [IQR] age, 78.5 [75.2-83.4] years, 77.02 [73.89-80.46] years, and 71.59 [64.76-76.06] years for sorafenib, chemoembolization, and reoperative hepatectomy or thermoablation, respectively), with a lower median (IQR) number of multiple recurrent nodules (1.00 [1.00-2.00] for sorafenib, 1.00 [1.00-2.00] for chemoembolization, and 2.00 [1.00-3.00] for reoperative hepatectomy or thermoablation). Extrahepatic recurrence was observed in 43.2% (n = 16) for sorafenib as the best potential treatment vs 14.6% (n = 89) for reoperative hepatectomy or thermoablation as the best potential treatment and 0% for chemoembolization as the best potential treatment. Those profiles were used to constitute a patient-tailored algorithm for the best potential treatment allocation.The herein presented algorithm should help in allocating patients with recurrent HCC to the best potential treatment according to their specific characteristics in a treatment hierarchy fashion.